Abstract
In the context of cross-disciplinary and cross-company cooperation, several challenges in developing manufacturing systems are revealed through industrial use cases. To tackle these challenges, two propositions are used in parallel. First, coupling technical models representing different content areas facilitates the detection of boundary crossing consequences, either by usinga posterioriora prioriconnection. Second, it is necessary to enrich these coupled technical models with team and organizational models as interventions focusing on the collaboration between individuals and teams within broader organizational conditions. Accordingly, a combined interdisciplinary approach is proposed. The feasibility and benefits of the approach is proven with an industrial use case. The use case shows that inconsistencies among teams can be identified by coupling engineering models and that an integrated organizational model can release the modelling process from communication barriers.
Highlights
Engineering projects are often subject to delay, cost overrun and quality problems or may even fail because of the lack of efficient information exchange between development teams
A combined approach is proposed for the cross-disciplinary modelling problem in cyber-physical production systems (CPPS)
We find that boundary crossing consequences can be more detected when technical models representing different content areas are coupled (Proposition 1)
Summary
Engineering projects are often subject to delay, cost overrun and quality problems or may even fail because of the lack of efficient information exchange between development teams. This led to additional efforts, cost and schedule delays In this case, the problem lay in the lack of a clear view on the organizational structure, information flows and interdependencies between the individual working units. We address the problem above and demonstrate the beneficial combination of two different concepts (Approaches A and B) to maintain associations and manage inconsistencies in interdisciplinary multi-team innovation processes. Either or both of the concepts can be chosen depending on the frequency of inconsistencies and the estimated costs of fixing them. A general problem statement and a combined approach of two propositions are introduced, followed by a real industrial use case explaining the challenges
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